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Finite-Horizon LQR Control of Quadrotors on $SE_2(3)$

Mitchell Cohen, Khairi Abdulrahim, James Richard Forbes

2020IEEE Robotics and Automation Letters78 citationsDOIOpen Access PDF

Abstract

This letter considers optimal control of a quadrotor unmanned aerial vehicles (UAV) using the discrete-time, finite-horizon, linear quadratic regulator (LQR). The state of a quadrotor UAV is represented as an element of the matrix Lie group of double direct isometries, SE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> (3). The nonlinear system is linearized using a left-invariant error about a reference trajectory, leading to an optimal gain sequence that can be calculated offline. The reference trajectory is calculated using the differentially flat properties of the quadrotor. Monte-Carlo simulations demonstrate robustness of the proposed control scheme to parametric uncertainty, state-estimation error, and initial error. Additionally, when compared to an LQR controller that uses a conventional error definition, the proposed controller demonstrates better performance when initial errors are large.

Topics & Concepts

Control theory (sociology)Linear-quadratic regulatorParametric statisticsRobustness (evolution)Nonlinear systemTrajectoryMathematicsQuadratic equationComputer scienceOptimal controlMathematical optimizationControl (management)PhysicsArtificial intelligenceGeneBiochemistryStatisticsAstronomyQuantum mechanicsChemistryGeometryAdaptive Control of Nonlinear SystemsDistributed Control Multi-Agent SystemsStability and Control of Uncertain Systems
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